I utilized exomePeak2 for peak detection in RNA samples and observed that many methylated regions corresponded to introns. This finding surprised me since I did not specify the mode argument, and according to my understanding, the default is set to "exon."
The workflow involved taking the exomePeak2 bed file output, converting it into a bigWig file, uploading it to the UCSC genome browser custom track, and subsequently discovering the presence of introns.
For this analysis, I used paired-end BAM files as input and an NCBI GTF file (ncbiRefSeq.gtf for Rattus norvegicus). The specified arguments in the exomePeak2 function were as follows:
start
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats
Attaching package: ‘MatrixGenerics’
The following objects are masked from ‘package:matrixStats’:
colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
colWeightedMeans, colWeightedMedians, colWeightedSds,
colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
rowWeightedSds, rowWeightedVars
Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics
Attaching package: ‘BiocGenerics’
The following objects are masked from ‘package:stats’:
IQR, mad, sd, var, xtabs
The following objects are masked from ‘package:base’:
anyDuplicated, aperm, append, as.data.frame, basename, cbind,
colnames, dirname, do.call, duplicated, eval, evalq, Filter, Find,
get, grep, grepl, intersect, is.unsorted, lapply, Map, mapply,
match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
Position, rank, rbind, Reduce, rownames, sapply, setdiff, sort,
table, tapply, union, unique, unsplit, which.max, which.min
Loading required package: S4Vectors
Attaching package: ‘S4Vectors’
The following objects are masked from ‘package:base’:
expand.grid, I, unname
Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: Biobase
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Attaching package: ‘Biobase’
The following object is masked from ‘package:MatrixGenerics’:
rowMedians
The following objects are masked from ‘package:matrixStats’:
anyMissing, rowMedians
Warning messages:
1: package ‘exomePeak2’ was built under R version 4.2.2
2: package ‘SummarizedExperiment’ was built under R version 4.2.2
3: package ‘MatrixGenerics’ was built under R version 4.2.1
4: package ‘BiocGenerics’ was built under R version 4.2.1
5: package ‘IRanges’ was built under R version 4.2.1
6: package ‘GenomeInfoDb’ was built under R version 4.2.3
7: package ‘Biobase’ was built under R version 4.2.1
Loading required package: AnnotationDbi
Warning messages:
1: package ‘GenomicFeatures’ was built under R version 4.2.2
2: package ‘AnnotationDbi’ was built under R version 4.2.2
Import genomic features from the file as a GRanges object ... OK
Prepare the 'metadata' data frame ... OK
Make the TxDb object ... OK
Warning message:
In .get_cds_IDX(mcols0$type, mcols0$phase) :
The "phase" metadata column contains non-NA values for features of type
stop_codon. This information was ignored.
Attaching package: ‘Biostrings’
The following object is masked from ‘package:base’:
strsplit
Extract bin features ... OK
Count reads on bin features ... OK
Identify background features ... OK
Estimate sample sepecific size factors from the background ... OK
Calculate bin GC contents on exons ... OK
Fit GC curves with smoothing splines ... OK
Calculate offset matrix ... OK
Detect peaks with GLM ... OK
GRangesList object of length 34629:
$`1`
GRanges object with 1 range and 0 metadata columns:
seqnames ranges strand
<Rle> <IRanges> <Rle>
1 chr4 154898070-154898094 +
-------
seqinfo: 80 sequences from an unspecified genome; no seqlengths
$`2`
GRanges object with 1 range and 0 metadata columns:
seqnames ranges strand
<Rle> <IRanges> <Rle>
2 chrM 7758-9382 +
-------
seqinfo: 80 sequences from an unspecified genome; no seqlengths
$`3`
GRanges object with 1 range and 0 metadata columns:
seqnames ranges strand
<Rle> <IRanges> <Rle>
3 chr12 31113498-31114297 -
-------
seqinfo: 80 sequences from an unspecified genome; no seqlengths
...
<34626 more elements>
Warning messages:
1: In .merge_two_Seqinfo_objects(x, y) :
Each of the 2 combined objects has sequence levels not in the other:
- in 'x': chr19_NW_023637714v1_random, chr19_NW_023637715v1_random, chrUn_NW_023637730v1, chrUn_NW_023637732v1, chrUn_NW_023637734v1, chrUn_NW_023637735v1, chrUn_NW_023637736v1, chrUn_NW_023637737v1, chrUn_NW_023637738v1, chrUn_NW_023637740v1, chrUn_NW_023637741v1, chrUn_NW_023637742v1, chrUn_NW_023637743v1, chrUn_NW_023637744v1, chrUn_NW_023637745v1, chrUn_NW_023637747v1, chrUn_NW_023637748v1, chrUn_NW_023637749v1, chrUn_NW_023637750v1, chrUn_NW_023637751v1, chrUn_NW_023637752v1, chrUn_NW_023637753v1, chrUn_NW_023637756v1, chrUn_NW_023637757v1, chrUn_NW_023637758v1, chrUn_NW_023637760v1, chrUn_NW_023637761v1, chrUn_NW_023637762v1, chrUn_NW_023637765v1, chrUn_NW_023637766v1, chrUn_NW_023637767v1, chrUn_NW_023637768v1, chrUn_NW_023637769v1, chrUn_NW_023637772v1, chrUn_NW_023637773v1, chrUn_NW_023637775v1, chrUn_NW_023637776v1, chrUn_NW_023637779v1, chrUn_NW_023637781v1, chrUn_NW_023637782v1, chrUn_NW_023637783v1, chr [... truncated]
2: In valid.GenomicRanges.seqinfo(x, suggest.trim = TRUE) :
GRanges object contains 36 out-of-bound ranges located on sequences
Ang,LOC108352909, LOC120094777, LOC103691088, LOC108351262,
LOC103693688, LOC120094123,Vof16, LOC102551251, LOC120097087,
LOC120098939, LOC108350834, LOC120095272, LOC120093965, LOC120094883,
LOC120097370, LOC120097467, LOC120094794, Galnt4, LOC120095229,
LOC108352196, LOC120100348, LOC120096115, LOC120096778, LOC120100476,
LOC120100393, LOC120103263, LOC120100962, LOC120093625, LOC102552101,
LOC120100737, LOC103692527, LOC120095249, LOC108350542, LOC120097094,
LOC120102858, LOC120095738, and LOC120093583. Note that ranges located
on a sequence whose length is unknown (NA) or on a circular sequence
are not considered out-of-bound (use seqlengths() and isCircular() to
get the lengths and circularity flags of the underlying sequences). You
can use trim() to trim these ranges. See ?`trim,GenomicRanges-method`
for more information.
finished.
I would greatly appreciate any suggestions or insights.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent